IEEE

Multiple-Input Floating-Point Adders: A Comprehensive Review

Abstract: Floating-point addition is pivotal in various computational applications, including scientific computing, machine learning, and graphics processing. Traditional two-input floating-point ...
Journal of Medical Internet Research

Longitudinal Model Shifts of Machine Learning–Based Clinical Risk Prediction Models: Evaluation Study of Multiple Use Cases Across Different Hospitals

Background: In recent years, machine learning (ML)–based models have been widely used in clinical domains to predict clinical risk events. However, in production, the performances of such models ...
Open Heart

Machine learning-based cardiovascular risk calculator for non-cardiac surgery

Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...
BMJ Open

Development and evaluation of a diagnostic aiding tool for differentiating tropical fevers using artificial intelligence approach: a study protocol from tertiary care hospital ...

Introduction Application of artificial intelligence (AI) tools in the healthcare setting gains importance especially in the domain of disease diagnosis. Numerous studies have tried to explore AI in ...
IEEE

Multiple-Input Multiple-Output Robust Control for Independent-Setup Variable Stiffness Actuator

Abstract: This letter presents the development of a multiple-input multiple-output (MIMO) coupling controller for the independent-setup variable stiffness actuator (VSA). The dynamic model of the ...
Fierce Healthcare

HHS' health tech arm wants input on how to accelerate adoption of AI in clinical care

The Department of Health and Human Services' (HHS') health tech arm wants to hear from the healthcare industry about ways to speed up the adoption of artificial intelligence in medical treatment. The ...